Experimental Study and Modeling of Automatic Home Energy Management System Using AI

dc.contributor.authorPiyanut Pranee
dc.contributor.authorNirudh Jirasuwankul
dc.date.accessioned2026-05-08T19:20:17Z
dc.date.issued2021-10-20
dc.description.abstractThis paper proposes an experimental study and modeling of Fuzzy logic based-AI for home energy management system. The management model has been designed for home in the subtropical climate zone-like, i.e., Thailand, which having yearly and monthly average temperature of 28°c and 30–38°c in the hottest season respectively. The studied system model comprises of the grid-connected load of home appliances, air conditioner, type-1 EV charger and solar rooftop PV supply. The objective of energy management is to minimize grid power consuming as well as maximizing solar PV utilization with 24-hour load profile, principally running of air conditioner and EV charging load. By testing the proposed management system comparatively to the generic system without managing scheme, energy saving of 43.90% can be achieved under the same operating and environmental conditions. Those are illustrated by the simulation results.
dc.identifier.doi10.1109/icpei52436.2021.9690647
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/17451
dc.subjectSmart Grid Energy Management
dc.subjectIoT-based Smart Home Systems
dc.subjectMicrogrid Control and Optimization
dc.titleExperimental Study and Modeling of Automatic Home Energy Management System Using AI
dc.typeArticle

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